Impacts on Atlantic Killifish from Neurotoxicants: Genes, Behavior, and Population-Relevant Outcomes.

Molecular, cellular, and organismal alterations are important descriptors of toxic effects, but our ability to extrapolate and predict ecological risks is limited by the availability of studies that link measurable end points to adverse population relevant outcomes such as cohort survival and growth. In this study, we used laboratory gene expression and behavior data from two populations of Atlantic killifish Fundulus heteroclitus [one reference site (SCOKF) and one PCB-contaminated site (NBHKF)] to inform individual-based models simulating cohort growth and survival from embryonic exposures to environmentally relevant concentrations of neurotoxicants. Methylmercury exposed SCOKF exhibited brain gene expression changes in the si:ch211-186j3.6, si:dkey-21c1.4, scamp1, and klhl6 genes, which coincided with changes in feeding and swimming behaviors, but our models simulated no growth or survival effects of exposures. PCB126-exposed SCOKF had lower physical activity levels coinciding with a general upregulation in nucleic and cellular brain gene sets (BGS) and downregulation in signaling, nucleic, and cellular BGS. The NBHKF, known to be tolerant to PCBs, had altered swimming behaviors that coincided with 98% fewer altered BGS. Our models simulated PCB126 decreased growth in SCOKF and survival in SCOKF and NBHKF. Overall, our study provides a unique demonstration linking molecular and behavioral data to develop quantitative, testable predictions of ecological risk.

Causes and consequences of pair-bond disruption in a sex-skewed population of a long-lived monogamous seabird.

Many animals form long-term monogamous pair bonds, and the disruption of a pair bond (through either divorce or widowhood) can have significant consequences for individual vital rates (survival, breeding, and breeding success probabilities) and life-history outcomes (lifetime reproductive success [LRS], life expectancy). Here, we investigated the causes and consequences of pair-bond disruption in wandering albatross (Diomedea exulans). State-of-the-art statistical and mathematical approaches were developed to estimate divorce and widowhood rates and their impacts on vital rates and life-history outcomes. In this population, females incur a higher mortality rate due to incidental fishery bycatch, so the population is male-skewed. Therefore, we first posited that males would show higher widowhood rates negatively correlated with fishing effort and females would have higher divorce rates because they have more mating opportunities. Furthermore, we expected that divorce could be an adaptive strategy, whereby individuals improved breeding success by breeding with a new partner of better quality. Finally, we posited that pair-bond disruptions could reduce survival and breeding probabilities owing to the cost of remating processes, with important consequences for life-history outcomes. As expected, we showed that males had higher widowhood rates than females and females had higher divorce rates in this male-skewed population. However, no correlation was found between fishing effort and male widowhood. Secondly, contrary to our expectation, we found that divorce was likely nonadaptive in this population. We propose that divorce in this population is caused by an intruder who outcompetes the original partner in line with the so-called forced divorce hypothesis. Furthermore, we found a 16.7% and 18.0% reduction in LRS only for divorced and widowed males, respectively, owing to missing breeding seasons after a pair-bond disruption. Finally, we found that divorced individuals were more likely to divorce again, but whether this is related to specific individual characteristics remains an important area of investigation.

Age × stage-classified demographic analysis: a comprehensive approach.

This paper presents a comprehensive theory for the demographic analysis of populations in which individuals are classified by both age and stage. The earliest demographic models were age classified. Ecologists adopted methods developed by human demographers and used life tables to quantify survivorship and fertility of cohorts and the growth rates and structures of populations. Later, motivated by studies of plants and insects, matrix population models structured by size or stage were developed. The theory of these models has been extended to cover all the aspects of age-classified demography and more. It is a natural development to consider populations classified by both age and stage. A steady trickle of results has appeared since the 1960s, analyzing one or another aspect of age × stage-classified populations, in both ecology and human demography. Here, we use the vec-permutation formulation of multistate matrix population models to incorporate age- and stage-specific vital rates into demographic analysis. We present cohort results for the life table functions (survivorship, mortality, and fertility), the dynamics of intra-cohort selection, the statistics of longevity, the joint distribution of age and stage at death, and the statistics of life disparity. Combining transitions and fertility yields a complete set of population dynamic results, including population growth rates and structures, net reproductive rate, the statistics of lifetime reproduction, and measures of generation time. We present a complete analysis of a hypothetical model species, inspired by poecilogonous marine invertebrates that produce two kinds of larval offspring. Given the joint effects of age and stage, many familiar demographic results become multidimensional, so calculations of marginal and mixture distributions are an important tool. From an age-classified point of view, stage structure is a form of unobserved heterogeneity. From a stage-classified point of view, age structure is unobserved heterogeneity. In an age × stage-classified model, variance in demographic outcomes can be partitioned into contributions from both sources. Because these models are formulated as matrices, they are amenable to a complete sensitivity analysis. As more detailed and longer longitudinal studies are developed, age × stage-classified demography will become more common and more important.

Analysis of transtheoretical model of health behavioral changes in a nutrition intervention study--a continuous time Markov chain model with Bayesian approach.

Continuous time Markov chain (CTMC) models are often used to study the progression of chronic diseases in medical research but rarely applied to studies of the process of behavioral change. In studies of interventions to modify behaviors, a widely used psychosocial model is based on the transtheoretical model that often has more than three states (representing stages of change) and conceptually permits all possible instantaneous transitions. Very little attention is given to the study of the relationships between a CTMC model and associated covariates under the framework of transtheoretical model. We developed a Bayesian approach to evaluate the covariate effects on a CTMC model through a log-linear regression link. A simulation study of this approach showed that model parameters were accurately and precisely estimated. We analyzed an existing data set on stages of change in dietary intake from the Next Step Trial using the proposed method and the generalized multinomial logit model. We found that the generalized multinomial logit model was not suitable for these data because it ignores the unbalanced data structure and temporal correlation between successive measurements. Our analysis not only confirms that the nutrition intervention was effective but also provides information on how the intervention affected the transitions among the stages of change. We found that, compared with the control group, subjects in the intervention group, on average, spent substantively less time in the precontemplation stage and were more/less likely to move from an unhealthy/healthy state to a healthy/unhealthy state.

The behavioural response of European seabass (Dicentrarchus labrax) to chlorinated seawater effluents.

Seawater chlorination is widely used for coastal, marine industries for the prevention of fouling. Using a choice chamber system, we investigated the influence of chlorinated seawater at typical concentrations occurring near chlorinated cooling water discharges, on the behaviour of juvenile seabass (Dicentrachus labrax). These studies showed that there was evidence of an effect of chlorination, with models predicting 22% fewer fish present in the chlorine dosed chamber compared to the undosed chamber in all control runs (mean number of fish in the dosed chamber in all control runs was 2.23 in comparison to 1.74 when chlorine was present). These data suggest that when food is available D. labrax will enter areas that are at mean chlorination levels of 0.04 mg l-1, which are typical close to the discharge of power station cooling water but are more likely to move away once the food supply is reduced.

Tour boats affect the activity patterns of bottlenose dolphins (Tursiops truncatus) in Bocas del Toro, Panama.

Bottlenose dolphins (Tursiops truncatus) of the Bocas del Toro archipelago are targeted by the largest boat-based cetacean watching operation in Panama. Tourism is concentrated in Dolphin Bay, home to a population of resident dolphins. Previous studies have shown that tour boats elicit short-term changes in dolphin behavior and communication; however, the relationship of these responses to the local population's biology and ecology is unclear. Studying the effects of tour boats on dolphin activity patterns and behavior can provide information about the biological significance of these responses. Here, we investigated the effects of tour boat activity on bottlenose dolphin activity patterns in Bocas del Toro, Panama over 10 weeks in 2014. Markov chain models were used to assess the effect of tour boats on dolphin behavioral transition probabilities in both control and impact scenarios. Effect of tour boat interactions was quantified by comparing transition probabilities of control and impact chains. Data were also used to construct dolphin activity budgets. Markov chain analysis revealed that in the presence of tour boats, dolphins were less likely to stay socializing and were more likely to begin traveling, and less likely to begin foraging while traveling. Additionally, activity budgets for foraging decreased and traveling increased as an effect of tour boat presence. These behavioral responses are likely to have energetic costs for individuals which may ultimately result in population-level impacts. Boat operator compliance with Panamanian whale watching regulations is urgently needed to minimize potential long-term impacts on this small, genetically distinct population and to ensure the future viability of the local tourism industry.

Evaluating different epidemiological models with the identical basic reproduction number ℛ0.

Epidemiological models with the identical basic reproduction number R0 may behave differently on both short time scale and long time scale. In this paper, we compare the predicted final sizes for several deterministic epidemic models and estimate the probabilities of a minor/major outbreak for continuous-time Markov chain (CTMC) models, all epidemic models have the identical R0 . It is proved that the final size predicted by the epidemic model with homogeneous mixing is larger than with heterogeneous mixing. For CTMC models with heterogeneous mixing, the probabilities of a minor outbreak initiated by superspreaders and non-superspreaders are calculated and compared. For both deterministic modelling and stochastic modelling, numerical simulations are performed to support the mathematical analysis.

Continuous time Markov chain approaches for analyzing transtheoretical models of health behavioral change: A case study and comparison of model estimations.

Continuous time Markov chain models are frequently employed in medical research to study the disease progression but are rarely applied to the transtheoretical model, a psychosocial model widely used in the studies of health-related outcomes. The transtheoretical model often includes more than three states and conceptually allows for all possible instantaneous transitions (referred to as general continuous time Markov chain). This complicates the likelihood function because it involves calculating a matrix exponential that may not be simplified for general continuous time Markov chain models. We undertook a Bayesian approach wherein we numerically evaluated the likelihood using ordinary differential equation solvers available from the gnu scientific library. We compared our Bayesian approach with the maximum likelihood method implemented with the R package MSM. Our simulation study showed that the Bayesian approach provided more accurate point and interval estimates than the maximum likelihood method, especially in complex continuous time Markov chain models with five states. When applied to data from a four-state transtheoretical model collected from a nutrition intervention study in the next step trial, we observed results consistent with the results of the simulation study. Specifically, the two approaches provided comparable point estimates and standard errors for most parameters, but the maximum likelihood offered substantially smaller standard errors for some parameters. Comparable estimates of the standard errors are obtainable from package MSM, which works only when the model estimation algorithm converges.

Model-based analysis of experimental data from interconnected, row-configured huts elucidates multifaceted effects of a volatile chemical on Aedes aegypti mosquitoes.

BACKGROUND: Insecticides used against Aedes aegypti and other disease vectors can elicit a multitude of dose-dependent effects on behavioral and bionomic traits. Estimating the potential epidemiological impact of a product requires thorough understanding of these effects and their interplay at different dosages. Volatile spatial repellent (SR) products come with an additional layer of complexity due to the potential for altered movement of affected mosquitoes and diffusion of volatile particles of the product beyond the treated house. Here, we propose a paired experimental design and statistical inference framework for estimating these nuanced effects of volatile SRs. METHOD: We fitted a continuous-time Markov chain model in a Bayesian framework to data on marked mosquitoes released in interconnected experimental huts conducted in Iquitos, Peru. We estimated the effects of two dosages of transfluthrin on Ae. aegypti behaviors associated with human-vector contact: repellency, exiting and knockdown in the treated space and in connected, adjacent huts. We validated the framework using simulated data. RESULTS: The odds of a female Ae. aegypti being repelled, and thus prevented from entering a treated hut (HT), increased at both dosages (low dosage: odds = 1.64, 95% highest density interval (HDI) = 1.30-2.09; high dosage: odds = 1.35, HDI = 1.04-1.67). The relative risk of exiting from the treated hut was reduced (low: RR = 0.70, HDI = 0.62-1.09; high: RR = 0.70, HDI = 0.40-1.06), with this effect carrying over to untreated spaces two huts away from the treated hut (H2) (low: RR = 0.79, HDI = 0.59-1.01; high: RR = 0.66, HDI = 0.50-0.87). Knockdown rates were increased in both treated and downstream huts, particularly under high dosage (HT: RR = 8.37, HDI = 2.11-17.35; H1: RR = 1.39, HDI = 0.52-2.69; H2: RR = 2.22, HDI = 0.96-3.86). CONCLUSIONS: Our framework is effective at elucidating multiple effects of volatile chemicals used in SR products, as well as their downstream effects. For the examined formulations of transfluthrin, we found notable dose-dependent effects on repellency, movement and knockdown that carry over to adjacent, untreated spaces.

Dose-Response Determination in Multistage Endpoint Clinical Trials.

Improper dose selection remains one of the key drivers of the large attrition rates observed in confirmatory studies in clinical drug development. Many factors contribute to this problem, such as insufficient resources allocated to dose-ranging studies and the use of statistical methods better suited for phase 3 studies than for dose selection. This paper describes a model-based dose-finding method that leverages all longitudinal data collected in the trial to estimate the dose-response relationship at any desired visit, using it to estimate target doses of interest, such as the minimum dose producing a desired clinical benefit. The approach uses a Markov chain model to account for correlation in the repeated measures obtained on the same patient. An actual phase 2 study and simulations are used to illustrate the methodology.

Mathematical methods to model rodent behavior in the elevated plus-maze.

The elevated plus maze is a widely used experimental test to study anxiety-like rodent behavior. It is made of four arms, two open and two closed, connected at a central area forming a plus shaped maze. The whole apparatus is elevated 50 cm from the floor. The anxiety of the animal is usually assessed by the number of entries and duration of stay in each arm type during a 5-min period. Different mathematical methods have been proposed to model the mechanisms that control the animal behavior in the maze, such as factor analysis, statistical inference on Markov chains and computational modeling. In this review we discuss these methods and propose possible extensions of them as a direction for future research.